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Issue 15, 2011
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A fully automated iterative moving averaging (AIMA) technique for baseline correction

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Abstract

Baseline correction is one of the pre-processing steps in the analysis of metabolite signals from chemometric analytical instruments. Fully automated baseline correction techniques, although more convenient to use, tend to be less accurate than semi-automated baseline correction. A fully automated baseline correction algorithm, the automated iterative moving averaging algorithm (AIMA), is presented and compared with three recently introduced semi-automated algorithms, namely the adaptive iteratively reweighted penalized least squares (airPLS), Asymmetric Least Squares baseline correction (ALS) and a parametric method, using NMR, Raman and HPLC chromatograms. AIMA’s potential in increasing the accuracy of multivariate analysis via SELTI-TOF and LCMS chromatograms was also assessed. The results show that the AIMA’s accuracy is comparable to these semi-automated algorithms and has the advantage of ease of use. An AIMA plug-in for an open source metabolomics analysis tool, MZmine, was also developed. The AIMA plug-in is available at http://padel.nus.edu.sg/software/padelaima.

Graphical abstract: A fully automated iterative moving averaging (AIMA) technique for baseline correction

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Supplementary files

Article information


Submitted
07 Oct 2010
Accepted
18 May 2011
First published
20 Jun 2011

Analyst, 2011,136, 3130-3135
Article type
Paper

A fully automated iterative moving averaging (AIMA) technique for baseline correction

B. D. Prakash and Y. C. Wei, Analyst, 2011, 136, 3130
DOI: 10.1039/C0AN00778A

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